My implementation of the original GAT paper (Veličković et al.). I've additionally included the playground.py file for visualizing the Cora dataset, GAT embeddings, an attention mechanism, and entropy histograms. I'll add an inductive example (PPI) soon as well.

Implementation and experiments of graph neural netwokrs, like gcn,graphsage,gat,etc.

[ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

Multi-turn dialogue baselines written in PyTorch

This is a PyTorch implementation of the GeniePath model in <GeniePath: Graph Neural Networks with Adaptive Receptive Paths> (https://arxiv.org/abs/1802.00910)

Graph Neural Networks

PyTorch code for ICPR 2020 paper "DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting"

Graph Convolutional Networks, Graph Attention Networks, Gated Graph Neural Net, Mixhop

中华人民共和国国家标准文档

The codes of our paper When to Talk: Chatbot Controls the Timing of Talking during Multi-turn Open-domain Dialogue Generation

GNN方法和模型的Pytorch实现。Pytorch implementation of GNN.

try different opts on word context graph with GCN and GAT to obtain word embeddings.

Pytorch implementation of graph attention network

Sentence Constituent-Aware Aspect-Category Sentiment Analysis with Graph Attention Networks (NLPCC 2020)

Link Prediction with Graph Neural Networks and Knowledge Extraction

Leveraging BERT GAT CRF to NER

A TensorFlow 2 implementation of Graph Attention Networks (GAT)

🎩 First experience with Gatsby & the JAM stack

Graph4CTR(GCNs, GATs, HGCNs)

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